• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.95-104
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• 2020

This study examines the effect of fintech on retail banks stock return listed in Indonesia Stock Exchange for the period of 2016-2018 as today's new technology lead to the emergence of fintech companies playing the same role as retail banks in the financial industry. This study is conducted quantitatively using monthly data from January 2016 to October 2018 and uses fintech as independent variable, proxied by fintech funding frequency and fintech funding value. Data transformation is conducted due to data volatility. The data of fintech funding, both frequency and value, is transformed into standardized fintech funding and growth of fintech funding. The data is obtained from Crunchbase, while the data of stock returns is obtained from Investing. This study further analyzes the data using Fama French Three-Factor Model and panel data regression. We found that fintech has no significant effect on retail banks' stock returns listed in Indonesia Stock Exchange for the period of 2016-2018. The findings of the study provide some useful insights in understanding fintech companies' current position to retail banks in Indonesia. This study also suggests banking institutions, fintech companies, policy-makers, and others to take advantageous steps in building inclusive financial sectors.

• Journal of Astronomy and Space Sciences
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• v.27 no.4
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• pp.279-288
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• 2010

To study properties of the pulsation in the infrared emission for long period variables, we have collected and analyzed the infrared observational data at M band for 12 OH/IR stars. We present the light curves using the data that cover about 30 years including recent observations of ISO and Spitzer. We use Marquardt-Levenberg algorithm to determine the pulsation periods and amplitudes and compare them with previous results of infrared and radio investigations. Generally, the newly determined pulsation parameters show much less errors because of the larger database. We find that the relationship between the pulsation period and amplitudes at M band is fairly well fitted with a simple linear equation in a wide period range. For OH 42.3-0.1, we find some evidences that the object could be a post-asymptotic giant branch star.

• Journal of The Korean Astronomical Society
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• v.24 no.1
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• pp.117-127
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• 1991

Here I report the confirmation of a long-term modulation of a period of $92^{+21}_{-13}$ years with the "time-delay correlation" method on the sunspot data compiled over the last a total of 289 years. This periodicity better specifies the cycle which falls pretty well within Gleissberg cycle, and clearly contrasts with the 55 year grand cycle which Yoshimura (1979) claimed. It is argued that the period-amplitude diagram method. which Yoshimura used, ana lysed peak amplitudes only so that a large number of data were disregarded, and thus was more susceptible to a bias. The planetary tidal force on Sun as for the possible cause to the solar activity was investigated and its possibility was ruled out in view of no period correlation between them.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1967-1971
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• 2007

In general, outflow is larger with rainfall but it is various in the initial moisture condition of basin and condition of rainfall distribution in both time and space. In this study, changes of outflow with time varied rainfall data were analyzed in the basin in which the moisture distribution is constant. Outflow differences with rainfall intensive of first period, middle period, and last period of month are 6.1% in January, 7.8% in February, 9.8% in March, 22.6% in April, 15.7% in May, 19.1% in June, 22.6% in July, 22.4% in August, and 16.8% in september respectably. The results show that 10 days outflow differences are ranged from 6.1% to 22.6% under the constant moisture condition, Outflow differences in the flood seasons are larger than them in the drought seasons.

• Asia-Pacific Journal of Business
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• v.12 no.2
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• pp.81-95
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• 2021

Purpose - The purpose of this paper is to examine the impact of holding period of IPOs on BHAR(CAR) of IPOs in IPO process, especially focused on business relationship of underwriters and institutional investors. Design/methodology/approach - This paper collected monthly IPO fund data in KOSDAQ during 2004 to 2012 and OLS(Ordinary Least Square) was hired to analyze the data. Findings - Underwriters do allocate IPOs with high BHAR(CAR) to business-related institutional investors holding IPOs longer to make the price of IPOs stable (market-making) for underewriters. Research implications or Originality - This paper finds the impact of holding period of IPOs on BHAR(CAR) of IPOs in IPO process, especially focused on business relationship of underwriters and institutional investors in Korea.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.329-330
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• 2023

The performance of the construction project is to be evaluated within 60 days of completion, according to relevant laws. It evaluates cost, construction period, design change, re-construction, safety, etc. for each project stage. And the project owners are inputting the evaluation results of the construction work into the construction project information system(CALS). The post-evaluation result information entered in this way can be referred to in the basic design of the construction project by referring to the related contents if there is a similar construction in the future. And It can also be used to predict and respond to the required period and cost by analyzing the accumulated data. In this study, in order to provide reference data that can be used in similar projects in the future, the latest analysis methods are reviewed and the possibility of future application is considered. Accordingly, this study intends to focus on the construction cost part among the indicators such as construction cost, construction period, design change, and re-construction that are currently being dealt with in post evaluation.

• Asian Oncology Nursing
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• v.1 no.2
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• pp.180-190
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• 2001

The purpose of this study is to compare the sexual behaviors of breast cancer survivors (BCS) with women without breast cancer (WWBC) and provide basic data to develop education program for patients before surgery. The study sample included 215 subjects: 140 women without breast cancer and 75 women diagnosed at least six months previously with breast cancer. Data were collected using the Wilmoth's Sexual behaviors Questionnaire-F that consisted of 50 items measuring sexually: communication, sexual techniques, sexual responses, body scare, self-touch, relationship quality, and masturbation. All items were scored on a 6-Likert scale with high scores reflecting high levels of the specific sexual behaviors. The reliability of this instrument was .91(Cronbach‘s alpha). Data were collected during the period from September 1 to September 30, 2001. The collected data were analyzed using t-test, Chi-square, ANCOVA with SPSSwin program. The scores of a sample of WWBC were compared to those of BCS and the scores of BCS were compared by type of surgery and period since surgery. The results were as follows: 1. No differences in sexual behaviors were found between BCS and WWBC, but, differences were found in communication, sexual technique, and relationship quality depending on the period since surgery. 2. Mean Score of BCS' communication in sexual behaviors was significantly lower than that of the WWBC. 3. Sexual behaviors scores of BCS with Menopause, lumpectomy, long duration since surgery showed significantly higher than that of the others. In conclusions, BCS returned to the normal sexual behaviors according to period since surgery. The program of the sexual counseling for patients before surgery should consider this result in the future.

• Journal of Korean Academy of Nursing
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• v.50 no.6
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• pp.837-847
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• 2020

Purpose: The purpose of this study was to investigate the effects of hospital characteristics on employment rate, working period, and retirement of ward nurses in Korea through a retrospective cohort study based on HIRAS data. Methods: Data were obtained from a report on medical care institutions of Health Insurance Review & Assessment Service (HIRAS). Data from 259,941 nurses who were working for a day or more from January 1, 2012, to December 31, 2016, at 2,942 medical care institutions were analyzed. Life table method analysis, Kaplan-Meier analysis, and Cox proportional hazard regression analysis were conducted. Results: The employment rates of 5 yeas and 10 years for the total sample were 38% and 28%, respectively. The estimated mean value of the working period was 3,642.7 days (SE: 17.4 days). Cox proportional hazard regression analyses revealed that nurses who were working at the general hospital/hospital, clinic, and nursing hospital were more likely to leave the hospital compared to those who were working at the 3rd general hospital. Nurses who were working at the medical institutions which were located in cities and countries, established by the private foundation, rated lower levels of nursing, and owned an insufficient number of beds, nurses and doctors were more likely to leave their workplace compared to those of the counterparts. Conclusion: This study indicates that hospital characteristics may play a significant role in retirement and working period of ward nurses in Korea. The improvement of hospital conditions to reduce ward nurses' retirement are needed.

• Journal of Fashion Business
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• v.23 no.3
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• pp.85-100
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• 2019

This study examines changes in consumer perceptions of fashion shows, which are critical elements in the apparel industry and a means to represent a brand's image and originality. For this purpose, big data in clothing marketing, text mining, semantic network analysis techniques were applied. This study aims to verify the effectiveness and significance of fashion shows in an effort to give directions for their future utilization. The study was conducted in two major stages. First, data collection with the key word, "fashion shows," was conducted across websites, including Naver and Daum between 2015 and 2018. The data collection period was divided into the first- and second-half periods. Next, Textom 3.0 was utilized for data refinement, text mining, and word clouding. The Ucinet 6.0 and NetDraw, were used for semantic network analysis, degree centrality, CONCOR analysis and also visualization. The level of interest in "models" was found to be the highest among the perception factors related to fashion shows in both periods. In the first-half period, the consumer interests focused on detailed visual stimulants such as model and clothing while in the second-half period, perceptions changed as the value of designers and brands were increasingly recognized over time. The findings of this study can be utilized as a tool to evaluate fashion shows, the apparel industry sectors, and the marketing methods. Additionally, it can also be used as a theoretical framework for big data analysis and as a basis of strategies and research in industrial developments.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.274-283
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• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.